Significance Canopy trees are keystone organisms that create habitat for an enormous array of flora and fauna and dominate carbon storage in tropical forests. Determining the functional diversity of tree canopies is, therefore, critical to understanding how tropical forests are assembled and predicting ecosystem responses to environmental change. Across the megadiverse Andes-to-Amazon corridor of Peru, we discovered a large-scale nested pattern of canopy chemical assembly among thousands of trees. This nested geographic and phylogenetic pattern within and among forest communities provides a different perspective on current and future alterations to the functioning of western Amazonian forests resulting from land use and climate change.

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Leaf mass per area (LMA) is a trait of central importance to plant physiology and ecosystem function, but LMA patterns in the upper canopies of humid tropical forests have proved elusive due to tall species and high diversity. We collected top-of-canopy leaf samples from 2873 individuals in 57 sites spread across the Neotropics, Australasia, and Caribbean and Pacific Islands to quantify environmental and taxonomic drivers of LMA variation, and to advance remote-sensing measures of LMA. We uncovered strong taxonomic organization of LMA, with species accounting for 70% of the global variance and up to 62% of the variation within a forest stand. Climate, growth habit, and site conditions are secondary contributors (1-23%) to the observed LMA patterns. Intraspecific variation in LMA averages 16%, which is a fraction of the variation observed between species. We then used spectroscopic remote sensing (400-2500 nm) to estimate LMA with an absolute uncertainty of 14-15 g/m2 (r2 = 0.85), or approximately 10% of the global mean. With radiative transfer modeling, we demonstrated the scalability of spectroscopic remote sensing of LMA to the canopy level. Our study indicates that remotely sensed patterns of LMA will be driven by taxonomic variation against a backdrop of environmental controls expressed at site and regional levels.

SummarySpectral properties of foliage express fundamental chemical interactions of canopies with solar radiation. However, the degree to which leaf spectra track chemical traits across environmental gradients in tropical forests is unknown.We analyzed leaf reflectance and transmittance spectra in 2567 tropical canopy trees comprising 1449 species in 17 forests along a 3400-m elevation and soil fertility gradient from the Amazonian lowlands to the Andean treeline. We developed quantitative links between 21 leaf traits and 400-2500-nm spectra, and developed classifications of tree taxa based on spectral traits.Our results reveal enormous inter-specific variation in spectral and chemical traits among canopy trees of the western Amazon. Chemical traits mediating primary production were tightly linked to elevational changes in foliar spectral signatures. By contrast, defense compounds and rock-derived nutrients tracked foliar spectral variation with changing soil fertility in the lowlands. Despite the effects of abiotic filtering on mean foliar spectral properties of tree communities, the spectra were dominated by phylogeny within any given community, and spectroscopy accurately classified 85-93% of Amazonian tree species.Our findings quantify how tropical tree canopies interact with sunlight, and indicate how to measure the functional and biological diversity of forests with spectroscopy.

Questions: Understanding distributions of tree species at landscape scales in tropical forests is a difficult task that could benefit from the recent development of satellite imaging spectroscopy. We tested an application of the EO‐1 Hyperion satellite sensor to spectrally detect the location of five important tree taxa in the lowland humid tropical forests of southeastern Peru. Location: Peru, Departamento de Madre de Díos. Methods: We used linear discriminant analysis with a stepwise selection procedure to analyze two Hyperion datasets (July and December 2006) to choose the most informative narrow bands for classifying trees. Results: Optimal channels selected were different between the two seasons. Classification was 100% successful for the five taxa when using 25 narrow bands and pixels that represented >40% of tree crowns. We applied the discriminant functions developed separately for the two seasons to the entire study area, and found significantly nonrandom overlap in the anticipated distributions of the five taxa between seasons. Conclusions: Despite known issues, such as signal‐to‐noise ratio and spatial resolution, Hyperion imaging spectroscopy has potential for developing regional mapping of large‐crowned tropical trees.